Written by Will Chen, the Developer of DeepGo

In ICO and IDO, participants are faced with the risk of a team’s being irresponsible, omissive, and even deceptive. Both mechanisms fail to create positive feedbacks and would ultimately expel good projects. Integrating the advantages of IDO and DAO, CDO minimizes risk by importing game theory and adapting the mechanism design of token behavioral economics.

Catalyzing shit coins in 2017, ICO made investors carousing in windfall profits and going crazy in bursting bubbles. In 2019, IEO debuted as a cash flow feast for centralized exchanges. Despite its endorsement from leading exchanges, IEO was also written in water. As DEX’s AMM innovative algorithm emerged in 2020, blockchain fundamentalists finally found their foothold. With IDO as its growth engine, the market of open finance greeted a new bull run.

ICO, IEO, and IDO are all means of low-cost financing through coin offerings on the blockchain. However, they would all ultimately lead to an imbalance in market regulation due to a lack of risk control mechanisms. Without a well-designed curation mechanism to filter out quality assets, they will eventually fall into the dilemma that good projects be driven out.

CDO, known as Collateralized DEX Offering, will be fully demonstrated in DeepGo Protocol V2. Equipped with the advantages of both IDO and DAO, this protocol enables NudgePool initiators to pledge for continuous liquidity growth. By providing participants with liquidity factor indicators, DeepGo establishes a DAO market governance model to sustain continuous fundraising and entrench risk management.

Based on AMM mechanism, DEX introduced a clever value unit model named pool. This mechanism has brought the blockchain out of the valley of death and has allowed DeFi to grow at a phenomenal rate.

However, problems remain, as IDO mechanism does not sustain the continuous liquidity growth of quality projects. Once liquidity vanishes, the IDO mechanism will fade. Rebalance between revenue and risk as its essence, DeFi is first generated by wealth creation effect and later it would center on filtering quality assets. During the process, IDO act as an incubator. However, a quality project desires a liquidity acceleration mechanism. Such a model should not rely on a centralized governance scheme since many serious problems, such as bribery of votes, exist.

The author will introduce a better IDO model that is based on IDO and is combined with the advantages of DAO. This would be more long-term friendly to all players in the market and would improve the robustness of the mechanism through quantitative risk signaling.

Compared with previous models, IDO is more transparent. AMM algorithm is showing signs that group governance is about to take shape. However, participants are only driven by high returns from initial mining and have not established a long-term balanced governance model.

DAO, Decentralized Autonomous Organization, is a brand-new form of organization based on the blockchain. This is not controlled by any individual but has a clear goal and can evolve continuously. With an application mechanism, DAO would function according to established procedures. However, DAO is not operated mechanically. It could maintain and upgrade itself according to the actual situation. During this self-adapting process, tokens play an integral role.

Being able to beat traditional industry, Internet platforms rely on active network effects. However, if blockchain platforms want to create more value, two factors are important: One is the positive network effect, and the other is the token incentive mechanism of DAO.

The behavioral economics of token focuses on three questions. What role does token play? What exact function does it have? What type of value capture is achieved? In addition to the three elements, the design of the token also takes the application of gaming behavior in the real scenario into consideration.

The CDO model created by DeepGo differs from traditional models of one-off fundraising in that there are three main types of roles in the protocol.

(1) Initial Provider (abbr. “IP”): IP provides a certain amount of project tokens as collateral. IP’s main motivation would be to receive continuous funding and to increase liquidity scale, namely, to obtain more base currency to enhance buying liquidity.

(2) Great Participant (abbr. “GP”): GP invests standard token as principle and provides buying liquidity. The main motive of GP is to obtain excess returns from the appreciation under the condition that the collateral is backed by a bet. This role demands personal cognitive ability and risk tolerance since GP bears the risk of the project. Therefore, GP could receive an additional performance mining bonus according to DeepGo protocol.

(3) Limit Participant (abbr. “LP”): LP invests standard token as principle and provides buying liquidity. The main motivation would be to receive a fixed return. In most cases, LPs are arbitrageurs. As they arbitrage, the size of NudgePool would increase rapidly.

IP only needs to impawn their tokens. This allows for more accurate pricing of project risk by introducing risk-hedging parameters. DeepGo employs a risk tranche model, which could meet different people’s risk preferences. Those with a high-risk preference could go for excess returns, while those with a low-risk preference could turn to stable returns with a transparent and relatively controlled risk.

DeepGo platform employs a risk tranche mechanism to secure gaming safety, namely, IP drives GP to screen high-quality assets by setting impawn rate, while GP drives LP to leverage through market signal regulation.

The platform uses the leverage ratio to regulate the benign growth of capital. Everyone could decide to invest or withdraw based on the current leverage ratio. Meanwhile, as the price of the project’s tokens escalates, the risk of its slumping would increase accordingly. In this case, the platform will gradually reduce the leverage for IPs to minimize their risk of closing out.

mt=etmax(GP , M/e0m0*((et /e0 )^1/2+α(et /e0 )))/M

Amongst:

M is the total token amount impawned by IP

GP is the total asset amount of GP

mt is the dynamic impawn ratio of IP

m0 is the initial impawn rate set by IP

e0 is the initial exchange rate: 1 denomination asset= e0Token

et is the exchange rate at moment t: 1 denomination asset= etToken

α is a platform parameter that could be adjusted through community governance

The leverage between GP and LP is mainly regulated by the reserve set aside by IP:

Lt=f(Rr)*f(Tr)/k

Amongst:

Lt is the dynamic leverage ratio of GP

f(Rr) is the retained ratio of subscription fees of IP

f(Tr) is the turnover rate of GP

k is the subscription fee rate of GP

Equipped with a risk tranche mechanism and based on the dynamic game of the free market, the platform can ensure that the leverage is reasonably manageable for all parties. The dynamic changes in leverage will assess liquidity risk comprehensively and act as feedback signals to market participants.

The value of filters lies in pricing risk and more in network effect. According to the network effect theory developed by economist Oz Shy, “winner takes all” is an important feature of market competition. In DeFi’s long-tail market, as curation continues to filter projects efficiently the positive network effect would be amplified and allowing the strongest to stay strong. In this way, the liquidity of token could grow continuously.

In DeepGo protocol, the curation mechanism is designed around the following principles:

(1) Unrestricted access: Users are free to access as any role at a low cost.

(2) Market regulation: Risk tranche is achieved through dynamic leverage and interest arbitrage. This allows users to give full play to their unique advantages of information, knowledge, resources, and capital so as to form an orderly and virtuous ecology.

(3) Motivation of evildoers: Every participant has the motivation to maximize his own interest, so there will inevitably be motivation for evildoing. NudgePool protocol agreement still cannot prevent vicious dumping of the project and inaction after fundraising. In this mechanism, the NudgePool agreement allows the gain of long-term project development to be greater than the short-term gain of evildoing. In addition, the parameters of the screening mechanism would be improved, for instance, raising the threshold of coin listing and increasing the weight of GP recommendation, so that quality projects can have more opportunities.

(4) Simplicity and completeness: Users do not need to participate in frequent interactions. They only need to go through the initial pool building process, and afterward, they only need to purchase and withdraw with a single click. Project parties would not occupy much community traffic and other resources, allowing the market to automatically filter out undesirable assets.

To IP, the positive network effect of high-quality assets results in a continuous inflow of subscription fees and accelerated liquidity growth. To participants, the filtering of project assets through leverage allows for lower matching costs and a more controlled risk warning. Through the positive feedback effect, quality assets are eventually screened out continuously, while other assets are automatically sifted out from the filtering mechanism.

DeFi has a huge market space with the trend of improving infrastructure such as oracle and synthetic assets, which will be combined with assets such as NFT. In this case, a sustainable liquidity solution is becoming more crucial than ever. ICO, IEO, and IDO models are all trapped by established models that are unsustainable in the long term. The CDO model combines the advantages of IDO and DAO to create a new possibility for optimum curation through market regulation mechanisms.

A quantitative researcher who all in blockchain in 2017, the author of this article was inspired by Vitalik Buterin’s 2018 article “Explanation of DAICOs” and happened to coincide with him in several ideas. Here, thank Vitalik Buterin for his inspiring works.